Photo Realistic Image Completion via Dense Correspondence

Annotation Propagation in Large Image Databases via Dense Image Correspondence

Prior Work This Work  Large training set of densely labeled images  Weakly supervised setup: use both image tags (cheaper to obtain) and labeled pixels (expensive to obtain)  Each image classified independently  Solve jointly for all pixels and classes  Use dense image correspondences to resolve visual ambiguities Fully tagged and labeled image database Sparsely tagged and (even not) label...

Photo-Realistic Talking-Heads from Image Samples

This paper describes a system for creating a photo-realistic model of the human head that can be animated and lip-synched from phonetic transcripts of text. Combined with a state-of-the-art text-to-speech synthesizer (TTS), it generates video animations of talking heads that closely resemble real people. To obtain a naturally looking head, we choose a “data-driven” approach. We record a talking...

3DFaceNet: Real-time Dense Face Reconstruction via Synthesizing Photo-realistic Face Images

With the powerfulness of convolution neural networks (CNN), CNN based face reconstruction has recently shown promising performance in reconstructing detailed face shape from 2D face images. The success of CNN-based methods relies on a large number of labeled data. The state-of-the-art synthesizes such data using a coarse morphable face model, which however has difficulty to generate detailed ph...

Dense Correspondence Estimation for Image Interpolation

Photo-Consistent Motion Blur Modeling for Realistic Image Synthesis

Motion blur is an important visual cue for the illusion of object motion. It has many applications in computer animation, virtual reality and augmented reality. In this work, we present a nonlinear imaging model for synthetic motion blur generation. It is shown that the intensity response of the image sensor is determined by the optical parameters of the camera and can be derived by a simple ph...